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Target tracking method based on multilayer time sequence filtering

A target tracking and target technology, applied in the field of computer vision, to achieve the effect of being conducive to expression and identification, improving robustness and improving accuracy

Active Publication Date: 2019-08-09
SOUTHWEST JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of this invention is to provide a kind of target tracking method based on multi-layer timing filtering, which can effectively solve the technical problems of relocation and tracking target when the tracking target disappears and reappears

Method used

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  • Target tracking method based on multilayer time sequence filtering
  • Target tracking method based on multilayer time sequence filtering
  • Target tracking method based on multilayer time sequence filtering

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Embodiment

[0027] The method of the invention can be used in various occasions of target tracking, such as intelligent video analysis, automatic human-computer interaction, traffic video monitoring, unmanned vehicle driving, biological group analysis, and fluid surface velocity measurement. The present invention will be further described below according to accompanying drawing:

[0028] Such as figure 1 and figure 2 As shown: the basic sequential network uses the Block3-Conv1 layer and Block4-Conv3 layer of the VGG-16 network as the spatial feature extraction part, and the LSTM network is used as the temporal feature extraction part; the input of the basic sequential network is two attentions containing the target Region image, that is, two target ROI images, the first target ROI image is regularized to a size of 128*128*3 pixels, and the second target ROI image is regularized to a size of 256*256*3 pixels; in the basic timing network, The first target ROI image and the second target RO...

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Abstract

The invention provides a target tracking method based on multilayer time sequence filtering, and relates to the technical field of computer vision mode recognition. The method comprises the followingsteps: step 1, selecting and determining a target object to be tracked from an initial image, step 2, a multi-layer time sequence filtering network comprising a basic time sequence network 1 and a basic time sequence network 2 which have the same network structure and are parallel to each other; step 3, carrying out multi-layer time sequence filtering network training, adopting an Adam optimization method for training, wherein the multi-layer time sequence filtering network has a target positioning capability; step 4, extracting a video image as an input image to be tracked; extracting frame images one by one as input images according to a time sequence; step 5, performing preliminary estimation on the target position through the basic time sequence network 1; and taking the initial imagein the step 1 as Ft, and taking the currently input frame image as Ft+1; step 6, accurately positioning the target through the basic time sequence network 2.

Description

technical field [0001] The invention relates to the technical fields of computer vision, artificial intelligence, pattern recognition and intelligent systems. Background technique [0002] Visual object tracking is an important research topic in the field of computer vision. Its main task is to obtain the continuous position, appearance and motion information of the object, and then provide the basis for further semantic analysis (such as behavior recognition, scene understanding, etc.). Target tracking research is widely used in intelligent monitoring, human-computer interaction, automatic control systems and other fields, and has strong practical value. At present, target tracking methods mainly include classical target tracking methods and deep learning target tracking methods. [0003] The classic target tracking methods are mainly divided into two categories: Generative Methods and Discriminative Methods. The generative method assumes that the target can be expressed ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/207G06T7/246G06N3/04G06N3/08
CPCG06T7/207G06T7/246G06N3/08G06T2207/10016G06T2207/20104G06T2207/20081G06N3/044G06N3/045
Inventor 权伟
Owner SOUTHWEST JIAOTONG UNIV
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